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(Senior) Data Engineer (m/w/d)

GALVANY · Berlin

On-siteMidPosted 2 Aug 2026

What this role requires

2 requirements, read out of the advert rather than guessed from the job title:

Also mentioned, not required: Kafka, Benthos, GoLang, PyTorch, Azure, GitHub, Linear, Notion, English, German. Worth having, but their absence is not what gets a CV filtered out.

See how often each of these is required across open data roles in Europe.

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Job description

At GALVANY , our goal is to make climate-neutral living a reality for everyone. We focus on execution – developing concrete, smart solutions and making heat pumps, battery storage, and smart metering easy to access, reliable, and affordable. GALVANY-Tech drives the energy transition through software. We're building an AI-based Operating System for sales, planning, installation and operation of heat pumps and integrated energy systems – from single-family homes to multi-unit buildings, and across our Energy Community as a Virtual Power Plant.

We are a profitable green-tech startup and believe that sustainable impact and long-term growth are only possible when grounded in a healthy business model. To implement our ambitious tech roadmap, we secured €10 million in seed funding from Set Ventures and AENU in the spring 2026. Driven by customer value, clarity, and responsibility, we stand for high-quality heating solutions and an environment where people take responsibility and drive lasting impact.

The Role

As a Data Engineer at GALVANY, you'll architect and maintain the data infrastructure that powers our AI-based Operating System. You'll process real-time energy data from heat pumps and integrated systems, build pipelines that fuel AI models and analytics, and ensure data quality across our entire ecosystem – from individual homes to our Virtual Power Plant.

Responsibilities:

Design and build scalable data pipelines using Kafka, Benthos, Clickpipes and related tools.

Read the full description (28 more sections)

Ensure data quality, consistency, and freshness across the energy ecosystem and internal processes.

Collaborate with ML engineers to deliver the right data in the right format for AI models.

Build monitoring and validation into pipelines from the start.

Translate business questions into data requirements and vice versa.

Leverage LLMs and AI tools to innovate data solutions and accelerate development.

Tech Stack: Data tools including Kafka, Benthos (data pipeline), Python, SQL; Backend with GoLang; ML with Python, PyTorch, and LLMs; General tools including Azure, GitHub, Linear, Notion.

Requirements

Experience. 4+ years of experience in high-performance environments (e.g. top-tier consulting, fast-scaling startups, or similar).

Track Record. Proven end-to-end responsibility in data engineering. From ideation to release.

Background. Strong background in relevant fields, e.g. Computer Science, Mathematics, Data Engineering, or similar.

Technical Skills. Strong coding skills with proficiency in Python and SQL. Experience with streaming architectures and data pipeline tooling. Fluent in spec-driven, AI-assisted development (e.g. Claude Code).

Mindset. Self-driven problem-solving mindset – no need for micromanagement or specific tickets.

Technical Aptitude. Technical mindset with a passion for understanding systems, data flows, and integrations, coupled with enthusiasm for continuous learning and problem solving.

Language. Fluent in English; German is a plus.

Skills and Qualities That Are Important to Us

Outcome-Led. You focus on value over volume. You embrace iteration, adapt quickly to new information, and prioritize what moves the needle for business and user.

Systems Thinker. You see the bigger picture. You understand how your work connects to the wider ecosystem – ensuring features contribute to a cohesive, scalable whole.

Pragmatic. You choose the simplest effective path to solve problems – especially by leveraging AI tools.

Customer Champion. You keep the end-user central in all decisions. You seek direct exposure to how customers experience the product.

Data Quality Guardian. You obsess over accuracy, freshness, and consistency. You build validation and monitoring into pipelines from the start.

Pipeline Architect. You design scalable data flows from source to insight. You balance real-time needs with batch efficiency.

Benefits

Strong Growth & High Impact. A unique opportunity to join during a hypergrowth phase and actively contribute to company success.

Compensation. Competitive salary and flexible perks (sports, mobility, learning) tailored to your needs.

Real-World Impact. Your work drives decarbonization – measurable in CO₂ savings, energy efficiency (kWh), and cost reductions (€).

Office. Prime location in Berlin Charlottenburg, regular company events and all-hands. We value in-person collaboration and connection, while partial remote work remains an option.

No Corporate Theater. Skip endless alignment meetings, politics and waiting for permission. You talk to the people who matter and ship.

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